AndreaBozzo/ceres-open-data-index huggingface dataset:
Participatory Processing Data on Pounded Yam generated by NRCRI in Nigeria

[Lien vers la fiche source] This dataset contains data generated during the Activity 4 or Step 3 - Participatory Processing Diagnosis and Quality Characteristics performed by the NRCRI team in Nigeria on Pounded Yam, within the RTBfoods project (following the [Methodological Guidance]). This dataset may contain diverse types of anonymized data (e‧g. questionnaires, processing parameters, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025) This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata.
Land use land cover ultra-high-spatial-resolution digital maps (5-cm) for 4 urban districts of the city of Bouaké (Air France, Belleville, Koko, Sossoribougou), center Côte d'Ivoire, 2020

[Lien vers la fiche source] This dataset provides ultra-high-spatial-resolution Land Use / Land Cover (LULC) digital maps of 4 urban districts of Bouaké, a city located in center Côte d'Ivoire (Ivory Coast). They were produced using images acquired by Unmanned Aerial Vehicles (UAVs) in 2020 at a spatial resolution of 5 cm. They were originally created to study the landscape determinants of the abundance of the main malaria mosquito species in these districts, and are made available here for a wide range of uses. These LULC products contain 8 land cover classes: bare soil, scrub, rice-growing surfaces, market gardening, dense deciduous trees, palm trees, completed buildings, unfinished buildings. The method used to generate the maps involved a supervised object-based image classification using aerial images acquired by an UAV, a ground-truth dataset acquired by photo-interpretation, and a random forest classifier. The classification accuracy varies from 91% to 94% depending on the district. In addition to the LULC georeferenced raster datasets of the four districts, we deliver the following files in this release: * the raster attribute table, including definitions of the land cover classes in English and French ; * a layer style (*.qml) to visualize the LULC georeferenced raster datasets in QGIS ; * a map of the LULC products as a .jpeg image (for visualization purposes only) ; * a map of the original orthophotos acquired by the UAV as a .jpeg image (for visualization purposes only) ; * representative pictures of the land cover classes ; * the detailed methodology used to generate the data, with the resulting confusion matrices (in English and French) ; * the ground-truth georeferenced datasets used for training and test in the classification (including the predictive variables).
Land use land cover very high resolution map (1.5-m) for the area of Diébougou, Burkina Faso, 2018

[Lien vers la fiche source] This dataset is a very-high spatial resolution Land Use / Land Cover (LULC) map of the region of Diébougou, located in southwestern Burkina Faso. Its spatial resolution is 1.5 m. It was produced in 2018 and made available for a wide range of uses. It contains 12 land cover classes: ligneous savanna, crop, grassland, marsh, riparian forest, woodland, rice, settlements, bare soil, main roads, permanent water bodies and running waters. The method used to generate the map involved a supervised object-based image classification using multisource satellite products (SPOT 7, Sentinel-2, a Digital Elevation Model), a ground-truth dataset acquired by fieldwork and photo-interpretation, and a random forest classifier. The classification accuracy is 84 %. In addition to the LULC georeferenced raster data, we propose the following files in this release: * the raster attribute table, including definitions of the land cover classes in english and french ; * a layer style (*.qml) to visualize the raster in QGIS ; * the map as a .jpeg image (for visualization purposes only) ; * representative pictures of the land cover classes ; * the detailed methodology used to generate the data, with the resulting confusion matrix (in English and French) ; * the ground-truth georeferenced dataset used for training and test in the classification ; * the R script used to create the product, based exclusively on Free and Open Source software.
Land use land cover very high resolution map (1.5-m) for the area of Korhogo, Côte d'Ivoire, 2018

[Lien vers la fiche source] This dataset is a very-high spatial resolution Land Use / Land Cover (LULC) map of the region of Korhogo, located in northern Côte d'Ivoire (Ivory Coast). Its spatial resolution is 1.5 m. It was produced in 2018 and made available for a wide range of uses. It contains 16 land cover classes: ligneous savanna, crop, marsh, riparian forest, dense forest, open forest, rice, cotton, fallows, cashew plantation, mango plantation, built-up, bare soil, main roads, permanent water bodies and running waters. The method used to generate the map involved a supervised object-based image classification using multisource satellite products (SPOT 6, Sentinel-2, a Digital Elevation Model), a ground-truth dataset acquired by fieldwork and photo-interpretation, and a random forest classifier. The classification accuracy is 83%. In addition to the LULC georeferenced raster data, we propose the following files in this release: * the raster attribute table, including definitions of the land cover classes in English and French ; * a layer style (*.qml) to visualize the raster in QGIS ; * the map as a .jpeg image (for visualization purposes only) ; * representative pictures of the land cover classes ; * the detailed methodology used to generate the data, with the resulting confusion matrix (in English and French) ; * the ground-truth georeferenced dataset used for training and test in the classification ; * the R script used to create the product, based exclusively on Free and Open Source software.
High throughput genetic diversity analyses of neglected crops: training data, codes and materials (Africa)

[Lien vers la fiche source] Marginal land is land that is of little agricultural value because crops produced there would be worth less than any rent paid for access to the area. Helping to develop such zones in Africa is a key goal for the [EU-funded EWA-BELT project]. The aim is to promote the sustainable intensification of agricultural production in organic, agroforestry and mixed crop and livestock farming systems in 38 study areas of six countries belonging to East and West Africa. The project will enhance current scientific knowledge on the adaptation of new and improved traditional crops in different agroecosystems and the impacts of traditional agricultural practices on soil health. This initiation to genomic data analysis with R was designed within the [EWA-BELT H2020 EU project (grant agreement ID 862848)]. The training module introduced to a variety of population genomics analyses for genotyping by sequencing (GBS) datasets. It included an introduction to single-nucleotide polymorphism (SNP) calling and filtering options, experimental design and various applications, population genomics statistics (genetic diversity and structure, Fst-based analyses) and genome-wide association studies (GWAS). The majority of the course consisted of practical R sessions to give hands-on experience of these analyses. Main topic and contents treated during the courses : Session 1. Passport data and Bioinformatics analysis Session 2. VCF filtering Session 3. Genetic diversity and structure Session 4. Genome-Wide Association Studies (GWAS) Each session includes a short introduction outlining the core concepts (PDF), R scripts (HTLM/PDF) and associated datasets.
Caractérisation fonctionnelle d'adventices en canne à sucre - 2023

[Lien vers la fiche source] Jeu de données caractérisant les espèces adventices rencontrées en canne à sucre sur l'essai nuisibilité différenciée comparant différents couverts d'adventices (lianes, dicotylédones, vivaces, fataques). Des traits fonctionnels aériens (SLA, LMC, LNC, SNC, LCC, SCC...) et racinaires ont été décrits.
Synthesis of the inventory of weeds of food crops in Côte d'Ivoire (2009-2016)

[Lien vers la fiche source] Synthesis of the weed inventory of food crops in the humid tropical climate regions of Côte d'Ivoire (2009-2016). Presence / absence synthesis by crop (rice, food crops, maize, plantain, cassava, yam, groundnut). This dataset covers 11 weed synthesis per crop for 494 weed species.
Base de données des organismes associés aux végétaux dans l’océan Indien

[Lien vers la fiche source] The Indian Ocean plant-associated organism database is the result of the common work of the regional members of the PRPV network. PRPV is a regional network for plant protection in the South West Indian Ocean. The database records the reports of plant-associated viruses, bacteria, fungi and arthropods observed in the Comoros archipelago, Madagascar, Mauritius, Reunion and Seychelles. The PRPV database was created in 2008 and was released online in 2011. Mainly devoted to agricultural pests and beneficial organisms, it also contains observations from natural ecosystems. It is possible to extract lists of organisms by host plant and by country from the database. It is also possible to create maps from geo-referenced observations. The PRPV database also hosts taxonomic information and regulations related to the organisms inventoried. The database records are made by field practicioners and national agriculture extension services. The data undergo a scientific and administrative validation before being publicly accessible.
Experimental filtration/compression dewatering kinetics of different cassava flours

[Lien vers la fiche source] Mechanical dewatering is a critical step in several food processing pathways, including in cassava flour processing. Compression dewatering kinetics are useful to design a dewatering operation. Such kinetics were measured in a filtration-consolidation cell, between 4 and 21 bar. They were measured on cassava from 3 origins, fragmented at 2 particle size distribution (PSD). The kinetics dataset comprises the filtrate mass, the cake length, the air pressure, the plug strength through the time ; the data of the moisture content measurement of the fresh and dewatered and of the filtrate. A python script is included to plot the dewatering kinetics from the dataset. Datasets can be used to help design dewatering equipment for cassava, possibly through a modeling approach. Combined with similar datasets measured on cassava of other qualities (PSD, variety, etc), or other products (e.g. yam), it could allow to determine a global model describing products compression dewatering.
Données pour l'évaluation de méthodes de géocodage

[Lien vers la fiche source] [FR] Ce jeu de données contient les toponymes de différents documents et leur référence dans le gazetier Geodict ([http://dx.doi.org/10.18167/DVN1/MWQQOQ]). Les documents utilisés proviennent de deux sources de texte : PadiWeb et AgroMada. [EN] This dataset contains the toponyms of various documents and their reference in the Geodict gazetteer ([http://dx.doi.org/10.18167/DVN1/MWQQOQ]). The documents used are from two text sources: PadiWeb and AgroMada.
Gendered Food Mapping Data on Boiled Yam generated by UAC-FSA & IITA  in Benin

[Lien vers la fiche source] This dataset contains data generated during the Activity 3 or Step 2 - Gendered food mapping - performed by the UAC-FSA & IITA team in Benin on Boiled Yam, within the RTBfoods project (following the [Methodological Guidance]). This dataset may contain diverse types of anonymized data (e‧g. questionnaires, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025) This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata.
Gendered Food Mapping Data on Boiled and Pounded Yam generated by NRCRI in Nigeria

[Lien vers la fiche source] This dataset contains data generated during the Activity 3 or Step 2 - Gendered food mapping performed by the NRCRI team in Nigeria on Boiled and Pounded Yam, within the RTBfoods project (following the [Methodological Guidance]). This dataset may contain diverse types of anonymized data (e‧g. questionnaires, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025) This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata.
Gendered Food Mapping Data on Boiled and Pounded Yam generated by Bowen University in Nigeria

[Lien vers la fiche source] This dataset contains data generated during the Activity 3 or Step 2 - Gendered food mapping performed by the Bowen University team in Nigeria on Boiled and Pounded Yam, within the RTBfoods project (following the [methodological Guidance]). This dataset may contain diverse types of anonymized data (e‧g. questionnaires, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025) This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata.
CLIFS 2021 (Crop LIvestock Farm Simulator)

[Lien vers la fiche source] Outil de simulation des exploitations de polyculture-élevage développé sous Excel® et visant à accompagner les producteurs dans leurs réflexions sur l'évolution stratégique de leurs systèmes de production. Peut également être utilisé en formation initiale et continue sur le thème de la polyculture-élevage, et par les chercheurs pour évaluer ex-ante les conséquences possibles d'innovations sur des exploitations réelles ou virtuelles. A également été utilisé pour représenter des bassins de collecte laitier ([https://agritrop.cirad.fr/596838/]). A simulation tool dedicated to mixed crop-livestock farms and developed under Excel® to support farmers in their reflections on the strategic evolution of their production systems. It can also be used in initial and continuing training on the theme of mixed crop-livestock systems, and by researchers to evaluate ex-ante the possible consequences of innovations on real or virtual farms. It has also been used to represent dairy supply areas.
Pratiques d'approvisionnement et de consommation d'huile de palme rouge par les ménages de Yaoundé, Cameroun

[Lien vers la fiche source] L’enquête a pour but de parcourir la diversité de situations de consommation, d’approvisionnement et d’utilisations de l’huile rouge. La ville de Yaoundé a été choisie pour réaliser cette enquête du fait de sa population cosmopolite, originaire des différentes régions du Cameroun, traditionnellement consommatrices ou non d’huile rouge. Notre échantillon de ménagères de Yaoundé a été raisonné pour couvrir une diversité de profils de ménagères et de profils économiques des ménages. La population couverte par l’enquête est donc de fait hétérogène sans viser à être représentative de la population de Yaoundé (pas de tirage aléatoire). Autour de l’unité de base « ménagère », l’objet d’étude est le ménage. A travers la ménagère, on s’intéresse aux habitudes de consommation, d’approvisionnement et d’utilisations du ménage dans son ensemble. Pour les restauratrices, nous nous sommes intéressés à la consommation d’huile, aux pratiques d’approvisionnement et aux utilisations de l’huile dans les pratiques du restaurant. Il s’agissait de comparer les logiques des restauratrices avec celles des ménagères.
NIRS Database on cooked freeze dried Sweetpotato for sugars at CIP, Uganda

[Lien vers la fiche source] Spectra of 60 cooked, freeze dried and milled SP genotypes from Uganda 2019. 3-4 fresh roots per genotype were boiled, mixed, freeze dried, milled and then scanned and sent to CIAT. Reference analyse was delayed at CIAT nearly 1 year due to Covid 19 pandemic and were just available by November 2020.
NIRS Database on cooked sweepotato for DM & sugars at CIP, Uganda

[Lien vers la fiche source] Spectra of 60 cooked fresh SP genotypes from Uganda 2019. 3-4 fresh roots per genotype were boiled, mixed, and then scanned. After that freeze dried and sent to CIAT. Reference analyse was delayed at CIAT nearly 1 year due to Covid 19 pandemic and were just available by November 2020.
NIRS Database on cooked sweetpotato for texture & cooking time at CIP, Uganda

[Lien vers la fiche source] Spectra of 61 SP genotypes. 3 cooked cubes per genotype were mashed and scanned by NIRS. Scans were used for calibration development. Reference analysis, cooking time and texture parameters, was done in Uganda directly before scanning. For texture parameters, the method was changed after sample 17, which means that sample IDs 02 to 17 were not considered for calibration development.
Hyperspectral calibration database on cooked cassava to predict dry matter content

[Lien vers la fiche source] This database contains 100 NIR average spectra of HSI images of cooked cassava root acquired in CIAT (Colombia), by using hyper spectral camera Specim FX17. Cassava roots were harvested from 07/03/2022 to 11/03/2022 in CIAT (Colombia) and analysed immediately after cooking. Twelve roots were used and each root is divided into six semicylinders. The semicylinders number 03,43,103 and 114 were used for HSI and DM measurements. Data was acquired using MEGHAR, K., DAVRIEUX, F., & ALAMU, E. (2020). SOP for Hyperspectral Imaging Analysis of Fresh RTB Crops. High-Throughput Phenotyping Protocols (HTPP), WP3. Montpellier, France: RTBfoods Project Report, 14 p.
SOP for analysis of cell wall polysaccharides from yam and plantain

[Lien vers la fiche source] Cell walls in plants are mainly composed of polysaccharides. Among them, pectin, cellulose and hemicellulose are composed of various sugars residues (acidic: galacturonic acid in pectins; or neutral: rhamnose, galactose, arabinose, xylose, glucose in cellulose, hemicellulose and pectin side chains). This fine composition impacts the structure but also the cooking behavior and mechanical properties of cell walls. This method seeks to determine the cell wall composition (neutral sugars composition and galacturonic acid content) of destarched AIS (Alcohol Insoluble Solid) extracted from raw and cooked yam and banana. It is applicable for AIS extracted from every fruit or vegetable product and containing a low amount of residual starch. For RTB products a destarching step is mandatory before analysis. First the samples are hydrolyzed in order to obtain sugar residues. Pectin and hemicellulose are degraded into their individual neutral and acidic sugars by a simple acid hydrolysis (hot concentrated sulphuric acid). In contrast, cellulose has to be solubilized under harsher conditions. For this reason, a double hydrolysis is performed. Afterwards, the free neutral sugars are derivatized into volatile alditol acetates before their separation in Gas Chromatography with a Flamme Ionization Detector (GC-FID). They are then quantified thanks to an internal standard of inositol. Whereas free galacturonic acid, transformed to its furfuric derivatives, is quantified by colorimetry after reaction with 3-phenylphenol (MHDP) which produces a fuschia pink complex with a maximum absorption at 520 nm. This SOP could be applied in all labs working on cell wall and pectins.
Gendered Gari/Eba product profile in Nigeria

[Lien vers la fiche source] The WP1 Gendered Food Product Profile for Gari-Eba in Nigeria reflects the final step ([step 5]) of an interdisciplinary five-step methodology developed to identify demand for quality characteristics among diverse user groups along the food chain ([Forsythe et al., 2022]). This methodology includes: [step 1)] interdisciplinary state of knowledge of the product ; [step 2)] gendered food mapping, which includes participatory research with men and women in rural communities regarding their product preferences and priorities; [step 3)] participatory processing diagnosis and quality characteristics ; and [step 4)] consumer studies in rural and urban areas of the product using different RTB varieties.
NIRS calibration database on fresh cassava puree to predict cooking time

[Lien vers la fiche source] This database contains 542 NIR spectra of cassava puree acquired in CIAT (Colombia), by using FOSS DS2500 NIR spectrometer. Cassava harvested at CIAT (Colombia) from various fields and years: 2022: 1 field "progeny" in January and February 2022. 2 harvests (trials) Field 202108CQQU2_ciat (M RTB): 22-02 and 22-05 on 12 Jan. and 8 Feb. 2022, repectively (10 and 11 MAP) This database contains also laboratory data measured on the same cassava roots samples: water absorption at 20 minutes of cooking (WA20) and water absorption at 30 minutes of cooking (WA30) the Dry matter values (DM) correspond to predicted values using a specific claibration developped by CIAT. Spectra included in this database have been acquired using: BELALCAZAR, J., TRAN, T., MEGHAR, K., & DAVRIEUX, F. (2021). NIRS Measurement on Fresh Ground Cassava. High-Throughput Phenotyping Protocols (HTPP), WP3. Cali, Colombia: RTBfoods Laboratory Standard Operating Procedure, 9 p.
Descriptive sensory analysis data for pounded yam in Nigeria

[Lien vers la fiche source] This file contains descriptive sensory data of pounded yam that was collected using panel trained following a [standardized methodology]. The data was collected by Bowen University team in Nigeria using RTBfoods [standard operating procedures] developed in work package 2 for the use by trained sensory panel. The cleaning of the data was conducted following guidelines as outlined in [RTBfoods manual].
Descriptive sensory analysis data for boiled plantain in Cameroon

[Lien vers la fiche source] This file contains descriptive sensory data of boiled plantain that was collected using panel trained following a [standardized methodology]. The data was collected by CARBAP team in Cameroon using RTBfoods standard operating procedures developed in work package 2 for the use by trained sensory panel. The cleaning of the data was conducted following guidelines as outlined in [RTBfoods manual].
Participatory Processing Data on Fried Sweetpotato generated by CIP in Nigeria

[Lien vers la fiche source] This dataset contains data generated during the Activity 4 or Step 3 - Participatory Processing Diagnosis and Quality Characteristics performed by the CIP team in Nigeria on Fried Sweetpotato, within the RTBfoods project (following the [Methodological Guidance]). This dataset may contain diverse types of anonymized data (e‧g. questionnaires, processing parameters, cleaned and processed data) which is to be available on open access following a 2-years embargo after the end of the RTBfoods project (embargo ending date: 15 March 2025) This dataset may also contain non-anonymized data (e‧g. raw data, consent forms signed by interviewees) which cannot be made publicly available, at any time; non-anonymized data is contained in the .tar‧gz file. For more information about the content of the .tar‧gz file, you are invited to contact the authors mentioned in the metadata.